SOTAVerified

Action Recognition

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

Papers

Showing 876900 of 2759 papers

TitleStatusHype
Excitation Backprop for RNNsCode0
Kronecker Mask and Interpretive Prompts are Language-Action Video LearnersCode0
SkateboardAI: The Coolest Video Action Recognition for SkateboardingCode0
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction RecognitionCode0
Joint Mixing Data Augmentation for Skeleton-based Action RecognitionCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Joint Discovery of Object States and Manipulation ActionsCode0
Joint-Partition Group Attention for skeleton-based action recognitionCode0
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer VisionCode0
Skeleton-Based Action Recognition With Directed Graph Neural NetworksCode0
Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional NetworksCode0
JOSENet: A Joint Stream Embedding Network for Violence Detection in Surveillance VideosCode0
Interpretable 3D Human Action Analysis with Temporal Convolutional NetworksCode0
Actor and Observer: Joint Modeling of First and Third-Person VideosCode0
DEAR: Depth-Enhanced Action RecognitionCode0
Investigation of Different Skeleton Features for CNN-based 3D Action RecognitionCode0
2D Pose Estimation based Child Action RecognitionCode0
DD-GCN: Directed Diffusion Graph Convolutional Network for Skeleton-based Human Action RecognitionCode0
Exploring Modulated Detection Transformer as a Tool for Action Recognition in VideosCode0
ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in VideosCode0
Interaction Relational Network for Mutual Action RecognitionCode0
ActivityNet: A Large-Scale Video Benchmark for Human Activity UnderstandingCode0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action RecognitionCode0
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video ArchitecturesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3Unverified
4DejaVidTop-1 Accuracy77.2Unverified
5InternVideoTop-1 Accuracy77.2Unverified
6InternVideo2-1BTop-1 Accuracy77.1Unverified
7VideoMAE V2-gTop-1 Accuracy77Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5Unverified
10TubeViT-LTop-1 Accuracy76.1Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7Unverified
2OmniVec23-fold Accuracy99.6Unverified
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
10LGD-3D Two-stream3-fold Accuracy98.2Unverified